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https://issues.apache.org/jira/browse/YARN-3415?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14394822#comment-14394822
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Hudson commented on YARN-3415:
------------------------------
FAILURE: Integrated in Hadoop-Mapreduce-trunk-Java8 #153 (See
[https://builds.apache.org/job/Hadoop-Mapreduce-trunk-Java8/153/])
YARN-3415. Non-AM containers can be counted towards amResourceUsage of a
fairscheduler queue (Zhihai Xu via Sandy Ryza) (sandy: rev
6a6a59db7f1bfda47c3c14fb49676a7b22d2eb06)
*
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/FSLeafQueue.java
*
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/FairScheduler.java
* hadoop-yarn-project/CHANGES.txt
*
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/FSAppAttempt.java
*
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/test/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/TestFairScheduler.java
> Non-AM containers can be counted towards amResourceUsage of a Fair Scheduler
> queue
> ----------------------------------------------------------------------------------
>
> Key: YARN-3415
> URL: https://issues.apache.org/jira/browse/YARN-3415
> Project: Hadoop YARN
> Issue Type: Bug
> Components: fairscheduler
> Affects Versions: 2.6.0
> Reporter: Rohit Agarwal
> Assignee: zhihai xu
> Priority: Critical
> Fix For: 2.8.0
>
> Attachments: YARN-3415.000.patch, YARN-3415.001.patch,
> YARN-3415.002.patch
>
>
> We encountered this problem while running a spark cluster. The
> amResourceUsage for a queue became artificially high and then the cluster got
> deadlocked because the maxAMShare constrain kicked in and no new AM got
> admitted to the cluster.
> I have described the problem in detail here:
> https://github.com/apache/spark/pull/5233#issuecomment-87160289
> In summary - the condition for adding the container's memory towards
> amResourceUsage is fragile. It depends on the number of live containers
> belonging to the app. We saw that the spark AM went down without explicitly
> releasing its requested containers and then one of those containers memory
> was counted towards amResource.
> cc - [~sandyr]
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